rohit211-s / emotion-based-personalized-recommendation-system Goto Github PK

Music is one of the most effective media as it can instill deep feelings and swamp listeners with subliminal messages. It deftly plays with our emotions which in turn affect our mood. Books, movies and television dramas are a few other media but, in contrast to these, music delivers its message in mere moments. Music is something which taps deeply into our emotional core as human beings. Thus, listening to good music can help us elevate our mood from a negative sense to a positive sense. It can aid us when we are feeling low and empower us. When we listen to sad songs, we tend to feel a decline in mood. When we listen to happy songs, we feel happier. Manual classification of songs based on mood, for making of a playlist, is time consuming and labour intensive. Using traditional music players, a user had to manually browse through his playlist and select songs that would soothe his mood and emotional experience. This task was labor intensive and an individual often faced the dilemma of landing at an appropriate list of songs. So we propose an automated system which help to minimize these efforts by suggesting the user a list of songs based on his current emotion. Emotion of the user can be easily guessed by looking at his face. For this purpose of face detection and emotion recognition, studying the features from his face is necessary. The system is provided with set of images which mainly contains the facial expression of the human. It then detects the emotion based on the scanned facial expression. Now based on the current emotion we recommend a list of songs which will enhance his mood as the songs keep playing.